code: def logmap0(y, c):
      """Hyperbolic logarithmic map at zero in the Poincare ball model.
  
      Args:
        y: Tensor of size B x dimension representing hyperbolic points.
        c: Tensor of size 1 representing the absolute hyperbolic curvature.
  
      Returns:
        Tensor of shape B x dimension.
      """
      sqrt_c = tf.sqrt(c)
      y_norm = tf.maximum(tf.norm(y, axis=-1, keepdims=True), MIN_NORM)
      return y / y_norm / sqrt_c * artanh(sqrt_c * y_norm)
  
file_path: neural-structured-learning/research/kg_hyp_emb/utils/hyperbolic.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 4 for calling a global function with example usage: logmap0(y, c) and returns: unknown